Robust Encoding of Local Ordinal Measures: A General Framework of Iris Recognition
Abstract
The randomness of iris pattern makes it one of the most reliable biometric traits. On the other hand, the complex iris image structure and various sources of intra-class variations result in the difficulty of iris representation. Although diverse iris recognition methods have been proposed, the fundamentals of iris recognition have not a unified answer. As a breakthrough of this problem, we found that several accurate iris recognition algorithms share a same idea — local ordinal encoding, which is the representation well-suited for iris recognition. After further analysis and summarization, a general framework of iris recognition is formulated in this paper. This work discovered the secret of iris recognition. With the guidance of this framework, a novel iris recognition method based on robust estimating the direction of image gradient vector is developed. Extensive experimental results demonstrate our idea.
Cite
Text
Sun et al. "Robust Encoding of Local Ordinal Measures: A General Framework of Iris Recognition." European Conference on Computer Vision, 2004. doi:10.1007/978-3-540-25976-3_25Markdown
[Sun et al. "Robust Encoding of Local Ordinal Measures: A General Framework of Iris Recognition." European Conference on Computer Vision, 2004.](https://mlanthology.org/eccv/2004/sun2004eccv-robust/) doi:10.1007/978-3-540-25976-3_25BibTeX
@inproceedings{sun2004eccv-robust,
title = {{Robust Encoding of Local Ordinal Measures: A General Framework of Iris Recognition}},
author = {Sun, Zhenan and Tan, Tieniu and Wang, Yunhong},
booktitle = {European Conference on Computer Vision},
year = {2004},
pages = {270-282},
doi = {10.1007/978-3-540-25976-3_25},
url = {https://mlanthology.org/eccv/2004/sun2004eccv-robust/}
}